Sound processor for a cochlear implant

ABSTRACT

The sound processor and method uses a model of basilar membrane motion to select stimuli, based upon the predicted motion which the acoustic signal presented would produce in an acoustically excited normally hearing cochlea. The filter; used, in contrast to single channel per electrode approaches, cover multiple channels and overlap with each other. Consequently the stimuli presented produce a neural excitation pattern which approximates the spatio-temporal travelling wave observed on the basilar membrane in an acoustically excited normally hearing cochlea. Preferably, the predicted electrode stimuli are based upon the instantaneous predicted amplitude of the electrode location.

TECHNICAL FIELD

The present invention relates to cochlear implants, and to soundprocessing devices and methods relating to cochlear implants.

BACKGROUND ART

In normal hearing, sound causes mechanical vibrations that stimulate thehair cells of the cochlea to produce electrical impulses that traveldown the auditory nerve where they are perceived by the brain as sound.If for some reason these hair cells are destroyed or not present withinthe cochlea, as is the case with individuals with severe or profoundhearing loss, the nerve cells do not receive this electricalstimulation, therefore no sound is perceived. A cochlear implantattempts to replace this lost function by providing artificialelectrical stimulation of the surviving auditory nerve. Cochlearimplants have been in clinical use for many years. Such devices use anarray of implanted electrodes to provide electrical stimuli to thecochlea The electrical stimuli are determined by a processor responsiveto speech and sound signals in the environment of the user.

Historically, prior to around 1994, the majority of speech processorsused in conjunction with a cochlear implant employed speech processingstrategies that can be described as Feature Extraction Strategies. Insuch strategies, the associated implant hardware attempts to identitythe speech features present in the detected sound signal and encodessuch features as patterns of electrical stimulation. Feature extractionstrategies have the advantage that the hardware required to perform thefeature extraction is relatively simple and consumes a relatively lowamount of power.

With improvements in silicon chip technology and an increased knowledgeof the safety of electrical stimulation, a new approach in soundprocessing became possible. This approach had the ability to provide afull range of spectral information of the speech signal without the needfor the hardware to fit the signal into a preconceived mould, giving thepatent the opportunity to listen to the particular information ofinterest, within background noise, providing a more realistic approachto speech processing. Such sound processors use band-pass filters toseparate acoustic signals into frequency bands or spectral componentswith relatively little overlap of the bands, with the electrodes beingstimulated in a tonotopic fashion according to the energy in thosebands. Usually they present a smoothed (low-pass-filtered)representation of the amplitude from each band to a single electrode.

Despite considerable practical success with each of the existingschemes, the user perceptions of existing devices indicate that thereare significant outstanding problems. Three fundamental problems ofsound perception reported by cochlear implant users are poor frequencyresolution and discrimination, poor perception of speech in noise at lowsignal-to-noise ratios, and poor perception of musical sounds.

It is an object of the present invention to provide an alternativespeech processor and processing method, in order to further improve thepractical performance of the cochlear implant system

SUMMARY OF THE INVENTION

In broad terms, the present invention provides a fundamental change tothe traditional approach used in sound processing for cochlear implants.Instead of attempting to separate acoustic information into discretefrequency bands or channels, the inventive processor produces electricalstimulation patterns that excite broad overlapping regions of thecochlea. It is believed that the approach of the present invention willprovide a better approximation to the behavior of the auditorystructures during hearing by a normally hearing listener. Currentprocessors produce localised stimuli based upon the frequency ofcomponents of the sound signal. In contrast, the present invention seeksto approximate the spatio-temporal neural excitation patterns which areinduced by the motion of the basilar membrane as a response to soundstimuli in the normally hearing listener. The present invention seeks toproduce a spatio-temporal pattern of stimulation along the length of anintra-cochlea electrode array, as opposed to merely localised stimuli.

According to a first aspect, the present invention resides in a methodof processing sound signals in order to generate electrical stimuli foran auditory prosthesis whereby a neural excitation pattern is producedwhich mimics the spatio-temporal pattern associated with the travellingwave observed on the basilar membrane in an acoustically excitednormally-hearing cochlea.

According to another aspect, the present invention provides a soundprocessor for use in a cochlear implant system, said sound processorbeing of the type which receives sound signals from a microphone or thelike, processes said signals according to a predetermined instructionset, and provides stimulation instructions for an Implanted electrodearray, characterized in that the predetermined instruction set producesstimulus instructions which are intended to provide an approximation tothe spatio-temporal waveforms induced in response to said sound signalson the basilar membrane of a normal hearing listener.

According to yet another aspect, the present invention provides a methodof processing sound signals so as to produce stimulus instructions for acochlear implant, including the steps of

deriving the vector of complex Fourier transform coefficients for a datasample;

multiplying the vector of the coefficients by a complex matrixrepresenting the amplitude and phase of the Fourier frequency componentsat the position of the electrodes in the cochlea relative to theamplitude and phase at the stapes in a normal ode to produce an outputvector; and

converting the output vector values to electrode current levels.

Travelling wave aspects of basilar membrane response have been observedand reported on in investigations of normal auditory processes. However,them has been no previous attempt to utilise these phenomena as anelement of stimulus processing for cochlear implants. The travellingwave may be thought of as a 3-Dimensional pattern in which thedimensions are time, distance along the basilar membrane, anddisplacement of the basilar membrane. The properties of these patternsthat are thought to be important (and different from existing processoroutputs) include a diagonal ridge structure of the 3D pattern, thedynamic nature of the ridge pattern that sweeps across the cochlearelectrode array at a particular velocity that depends on position, thesmoothly varying nature of the pattern in both space and time, and themaintenance of naturally-occurring phase and amplitude relationshipsbetween the stimulation patterns on individual electrodes.

BRIEF DESCRIPTION OF DRAWINGS

The implementation of the present invention will be described in moredetail with reference to the accompanying drawings, in which:

FIG. 1 is a graph illustrating a travelling wave excitation patternproduced in response to a pure tone of frequency 200 Hz;

FIG. 2 is a graph illustrating a travelling wave excitation pattern fortones at 200 and 600 Hz;

FIG. 3 is a graph illustrating a travelling wave excitation pattern fortones at 470 and 200 Hz;

FIG. 4 is a schematic illustration of one implementation of theinvention;

FIG. 5 is a block diagram of one speech processing implementation of thepresent invention;

FIG. 6 is a graph of the typical frequency response of a 22-channelfilterbank;

FIG. 7 is a graph depending the typical delay of each of each of the 22channels;

FIG. 8 is a block diagram showing the sub-components of the ElectricalEncoding Component of FIG. 5.

DETAILED DESCRIPTION

The present invention will be described with reference to the hardwareimplementation used by the applicant, using an Implantedreceiver/stimulator unit and an external speech processor andmicrophone. However, the present invention is of broad scope and can beimplemented on any sufficiently sophisticated cochlear implant system.In particular, it is anticipated that the present invention will be ableto be implemented more fully and in more detail on future generations ofcochlear implants, with increased processing power and flexibilityrelative to the current state of the art. The present invention couldalso be implemented in a totally implanted device, or some intermediatestage between the present systems and a totally implanted device.

The essential difference between the invention described and previousimplant coding schemes is that the importance of overlapping informationacross electrodes is recognized and a complex spatio-temporal pattern isproduced. This pattern preserves, at least in part, the detailedamplitude and phase relationships between different positions that occurnormally in an intact cochlea. These amplitude and phase relationshipsvary smoothly as a function of position along the cochlea to produce theacoustic “travelling wave” (von Bekesy, 1961). Instead of attempting toseparate acoustic information into discrete frequency bands or channels,the travelling wave processor produces electrical stimulation patternsthat excite broad overlapping regions of the cochlea. As an example,FIG. 1 shows the excitation pattern that is produced by the inventivetravelling wave processor in response to a pure tone input signal. Eachline in the Figure shows the shape of the excitation function at aninstant in time. The horizontal axis represents position along thecochlea from the basal (high frequency) end on the left to the apical(low frequency) end on the right.

In contrast the excitation pattern produced by the same pure tone inputsignal after processing by any of the currently used cochlear implantcoding schemes would be localized to one position in the cochlea andrepresented by a narrow ridge running vertically up the page in a Figureanalogous to FIG. 1. In some cochlear implant coding schemes theamplitude of the vertical ridge would be represented by electricalpulses at a fixed rate and level (ACE, SPEAK), or modulated at a rateequal to the frequency of the (low-frequency) input tone (F0F2, F0F1F2,MPEAK, CIS, SAS). In the latter cases, the excitation pattern iseffectively a vertical slice taken from the pattern of FIG. 1 at thepoint where the amplitude of the pattern is greatest.

It is hypothesized that the auditory pathways of the brain havespecialized perceptual mechanisms designed to recognize characteristicsof 3-dimensional (position X time X amplitude) excitation patterns likethose shown in FIG. 1. If is known that the visual and tactile sensorysystems have neural mechanisms specialized to detect the orientation andspacing of stripes and ridges. The auditory system may be programmed inan analogous manner to recognise the diagonal ridges of patterns likethe one in FIG. 1. If an incomplete pattern is presented to the cochlea(as in all prior art cochlear implant coding schemes) these perceptualmechanisms will be engaged but will not operate as effectively as theywould if the whole pattern was presented. It is hypothesized that thepresentation of complete 3D patterns will improve the perception ofsound by cochlear implant users and overcome or reduce some of theproblems that are common to all prior art cochlear implant systems.Relative to normal hearing listeners, the problems for implant usersinclude poor frequency discrimination and resolution abilities, poorspeech recognition of speech in background noise, and lack of musicalquality for processed musical sounds.

When the stimulation is viewed as a 3D pattern, several consequencesbecome more apparent

a) A whole pattern is easier to recognize than a partial pattern becauseit contains more information. This characteristic is also important forgrouping sound components from the same source. Some of the temporal andspatial coherence of excitation patterns arising from a single soundsource is lost when the signal is bandpass filtered into separatecomponents that are encoded independently of one another. Conversely,sounds from different sources will be easier to separate if each onegives rise to a whole pattern, rather than a number of independentcomponents which must be recombined by the perceptual mechanism into anunknown number of sound sources. In the particular case of speech inbackground noise, it is important that the speech and the noise bothproduce complete 3D excitation patterns so that the perceptualmechanisms can use this information to allocate components of thecombined pattern more easily to the noise or to the speech.

b) Dynamic patterns are easier to recognise than stationary ones. If iswell-known that the tactile system provides increased information abouttexture, shape and edges of objects if the fingers are moved over thesurface of the object than if a static contact is made. In a similarway, the spacing of ridges in the 3D auditory excitation pattern may beenhanced perceptually by sweeping them along the cochlea. Similarly,onsets and offsets of sounds correspond to edges in the 3D pattern, andthese may be perceived more clearly as they move along the cochlea,rather than just appearing with different amplitudes at different partsof the cochlea and then disappearing again. Thus the presentation ofdynamic patterns may improve frequency discrimination and resolution andperception of onsets and offsets of sounds with complex spectra.

c) If a pattern is known to vary smoothly and regularly, missingsections can be interpolated or filled in. For example, one can “see”what is on the other side of a paling fence as one walks past eventhough most of the scene is obscured by the fence at any one time. Thisis because the visual system is able to reconstruct the continuouspicture from the parts that are viewed at separate instants in time. Inthe case of auditory signals that are obscured by noise, parts of asmoothly varying, regular speech pattern may be perceived throughtemporal and spectral gaps in the noise and reconstructed in ananalogous manner. However, if the speech and noise patterns do not varysmoothly with position, this reconstruction is much more different thisis a potential explanation for the fact that implant users are unable torecognize speech in noise when the signal-to-noise ratio is close tozero. The travelling wave processor may allow listeners to reconstructlower amplitude speech signals even when they are partially obscured bymore intense noise signals, provided that there are some temporal orspectral gaps in the noise signal.

d) Tone complexes with harmonically related components produce 3Dpatterns with special characteristics in the regions where the tonalpatterns overlap. These characteristics are not present in anharmoniccomplexes. They are also not present in the excitation patterns producedby existing cochlear implant sound processors because they do notproduce overlapping patterns for individual tones separated by an octaveor more. For example, FIG. 2 shows the excitation pattern for 2 tones at200 and 600 Hz. In the overlap region, every third diagonal ridge islarger than the others because of the constructive addition of the twoexcitation patterns. FIG. 3 shows an anharmonic combination where thereis no regular summation of the two patterns in the overlap region.

The travelling wave in normal hearing has been recognised and discussedin the scientific literature. However, this literature has had virtuallyno effect on the design of cochlear implants or hearing aids as tar asthe inventors are aware. One explanation for this is that the frequencyresponse of the cochlea to sinusoidal signals is highly peaked andimplant and hearing aid designers have chosen to ignore thelow-frequency tails of the frequency response curves. The closestexisting technologies are cochlear implant sound coding schemes thatmeasure spectral characteristics of input signals with bandpass filtersand represent them by stimulating individual electrodes.

The preferred implementation of the present invention utilizes adigital-signal-processor to calculate an approximate travelling waveexcitation pattern from a digitised input signal. The travelling wavepattern is essentially a specification of the displacement of each pointon the basilar membrane of the cochlea as a function of time andposition. The implementation is based directly on published experimentaldata from normally-hearing human subjects rather than theoretical modelsof basilar membrane mechanics. The implementation is also simplified tomake it feasible for real-time implementation and to make it easier toparameterize the fitting procedure for individual cochlear implantusers.

One embodiment of the system according to the present invention is shownin FIG. 4, with the components of the system as listed below.

1. Microphone 11 to convert an acoustic input signal to an electricalsignal

2. Preamplifier/Automatic Gain Control 12 to amplify and control thelevel of the electrical signal.

3. Analog-to-Digit-Converter 13 to convert the electrical signal to astream of digital samples.

4. Digital-Signal-Processor 14 to calculate the travelling wave patternand convert it to an electrical stimulus pattern.

5. Programmable Memory 15 to store patient-specific parameters, theprocessor programs, and intermediate results in calculating thetraveling wave pattern.

6. Output Signal Generator 16 to control a cochlear implant and deliverthe electrical stimulus to the implant patient

A simpler version of the present invention, in particular the digitalsignal processor, is shown in FIG. 5. In this particular aspect theinvention essentially resides in a system consisting of four main parts,a Basilar Membrane Motion Model which accepts an audio signal as inputand calculates the displacement or velocity of the basilar membrane ateach electrode position; an Inner Hair Cell Model which calculates theamount of neural excitation at each electrode position based on theinformation received from the Basilar Membrane Motion Model; an OuterHair Cell Model which provides a feedback path that takes intoconsideration the amount of neural excitation calculated by the InnerHair Cell Model and the affects such excitation will have on the BasilarMembrane Motion Model; whereby the amount of neural excitation affectsthe response of the Basilar Membrane Motion Model; and an ElectricalEncoding Component which calculates the pattern of electricalstimulation which will provide the desired neural excitation pattern.Each of these 4 components will be described in more detail below.

Basilar Membrane Motion Model

The Basilar Membrane Motion Model accepts an audio signal as input andis calculates the displacement or velocity of the basilar membrane ateach electrode position in relation to the audio signal.

One possible embodiment of the Basilar Membrane Motion Model consists ofthe following steps, which are repeated continuously:

1 The input audio signal is divided into short overlapping frames. Eachframe contains L consecutive samples of the audio signal, and is definedas the column vector X1. A suitable length is L=128. Each frame heavilyoverlaps with the previous frame, and contains K new data points. Asuitable value is K=1.

2 Multiply the input frame vector X1 point-by-point by a window vectorW, resulting in a column vector X2 of length L, according to:X2(n)=X1(n)*W(n)for n=0 to L−1.

A suitable window function is the Hann function, defined as:W(n)=0.5*(1−cos(2*n*pi/L)for n=0 to L−1.

3 Calculate the L-point Fast Fourier Transform (FFT) of Me column vectorX2. This results in a column vector X3 of length L, with complex values.Because X2 is real, X3 has Hermitian symmetry, and the last L/2 samplescan be discarded (or not calculated). From the first L/2 samples, onlythe real parts are required and the imaginary parts are discarded (ornot calculated). The output is a real column vector X4 of length L/2.

4 Multiply column vector X/4 by a rectangular weights matrix G,according to:X5=G*X4.

The weights matrix G has N rows and L/2 columns. The output is a columnvector X5 of length N, where N is the number of channels. The weightsmatrix G determines the frequency magnitude response of each channel,and is further described below.

5 Delay each channel by a time delay specified by column vector D, whichhas length N, according to the formula:X6(k,t)=X5(k,t−D(k))for k=1 to N

Typical delays for a 22-channel processor are shown in FIG. 7. The delayvaries from zero delay at channel 1 (the most basal channel to 8milliseconds at channel 22 (the most apical channel).

The output is a column vector X6 of length N, where each element is asample of one channel of the Basilar Membrane Motion Model.

Each row of the matrix W represents the amplitude and phase of the FFTfrequency components at the position of one of the electrodes in thecochlea relative to the amplitude and phase at the stapes (the input tothe cochlea). The phase difference is equal to 2 pl times the time takenfor the travelling wave to travel from the stapes to the position of theelectrode multiplied by the frequency of the FFT component. Theamplitude difference between the stapes and the electrode position isproportional to the response of the basilar membrane at the position ofthe electrode to a pure tone at the frequency of the FFT component (oralternatively, the tuning curve of a neuron at the position of theelectrode). The amplitude coefficients at each electrode position have apeaked shape with the maximum at the FFT frequency closest to thecharacteristic frequency at the individual electrode position, and theamplitudes of FFT coefficients higher than this frequency fall rapidlyto zero.

An alternative way of implementing the delays in this system is byshifting the FFT window back in time by a different amount for eachelectrode. If the shift is chosen to be equal to the time taken for thetravelling wave to travel from the stapes to the electrode position,then the coefficients of the matrix W are all real (ie the phase is zerofor all FFT components).

The weights matrix G can be calculated according to the following steps:

1. The characteristic frequency of each channel is determined based onthe position of the electrodes in the cochlea, according to Greenwood'sformula. A further correction to the should be applied to account forthe fact that electrodes at a particular position in the cochleaactually stimulate neurons with a lower characteristic frequency thanthat predicted by Greenwood's formula (Blarney P J, Dooley G J, Parisi ES and Clark G M., Pitch comparisons of acoustically and electricallyevoked auditory sensations. Hearing Research, 99, 139-150, 1996; JamesC, Blarney P J, Shallop J K, Incerti P V & Nicholas A M. Contralateralmasking in cochlear implant users with residual hearing in thenon-implanted ear, audiology and Neuro-Otology, 6, 87-97, 2001). Thiscorrection factor implies that the effective distance of the electrodefrom the stapes is greater by a factor of 2.625/1.875. Alternatively,for subjects who have previously used another sound processor and havebecome accustomed to a particular frequency-to-electrode map, thosefrequencies can be used. The characteristic frequencies are stored in avector C of length N.

2. The centre frequency of each FFT bin is calculated and stored invector B, of length L/2.

3. The weights matrix element G(k, b) represents the gain of channel kat the centre frequency of FFT bin b, and can be calculated according tothe formula:B(b)<=C(k)G(k, b)={B(b)/C(k)}ˆEelseG(k, b)=0where the symbol “ˆ” means “to the power of” and the parameter E iscalled the gain exponent. Suitable values for E are in the range 1 to 5.Suitable choices for characteristic frequencies for 22 channels, with again exponent E=1 result in the magnitude response shown in FIG. 6.

The amplitude of each FFT component at each electrode position isrepresented by the magnitude of the corresponding element in matrix W.These amplitudes may be estimated from psychophysical tuning curves inhumans with normal hearing (Zwicker, E. On a psychophysical equivalentof tuning curves. In Zwicker E. & Terhardt E (eds) Facts and models inhealing. pp 132-141, Berlin: Springer-Verlag, 1974), from estimates ofexcitation in the loudness models of Zwicker (Zwicker E. Masking andpsychological excitation as consequences of the ear's frequencyanalysis, in Plomp R & Smoorenburg G F (Eds) Frequency analysis andperiodicity detection in hearing, pp 376-96, Leiden: A W Sijthoff,1970.) or Moore & Glasberg (Moore B C J & Glasberg B R. A model ofloudness perception applied to cochlear hearing loss. AuditoryNeuroscience 3, 289-311, 1997) or from an approximation or from anempirical function designed to optimise the travelling wave processorfor individual implant users.

Inner Hair Cell Model

The Inner Hair Cell Model calculates the amount of neural excitation ateach electrode position based on the displacement or velocity of thebasilar membrane at each electrode position in relation to the audiosignal as calculated by the Basilar Membrane Motion Model as discussedabove. A simple embodiment of the Inner Hair Cell Model is a half-waverectifier, with other embodiments possible as would be obvious to thoseskilled in the art. The half wave rectification mimics the response ofthe hair cells in a normal cochlea. The amplitude of the half-waverectified travelling wave at each electrode position is represented bythe current level (or electric charge, or pulse width) of an electricpulse on that electrode. This mapping from amplitude to electricalstimulation parameters differs from conventional cochlear i5mplantmapping in that the instantaneous amplitude of the travelling wave isrepresented rather than a smoothed amplitude or intensity which isaveraged over a time window of several milliseconds. Conventionalprocessors code the amplitude envelope rather than the instantaneousamplitude, and in doing so, they lose much of the temporal informationcarried by the signal itself. The coding of instantaneous amplitude isespecially important to the travelling wave processor because codingenvelope information would merely smear out the information fromdifferent frequency components rather than providing the detailed timinginformation illustrated in FIGS. 1-3. In particular the 3-dimensionalridges would become much broader in both spatial and temporaldimensions, and would lose their characteristics.

Outer Hair Cell Model

The Outer Hair Cell model aims to emulate the non-linearity that isobserved in the response of a person with normal hearing. This isperformed by providing a feedback path to the Basilar Membrane MotionModel which takes into consideration the proposed neural excitationpattern and the affects such a pattern has on the response of theBasilar Membrane Motion Model. The output of the Inner Hair Cell Modelis an estimate of the neural excitation pattern that would be present ina person with normal hearing. It has been found that the gain forlow-amplitude audio signals is greater than the gain for large-amplitudeaudio signals. This component is optional and may be omitted in asimplified implementation.

Electrical Encoding Component

The Electrical Encoding component calculates the pattern of electricalstimulation that will provide the desired neural excitation pattern.There are several possible embodiments of the Electrical Encodingcomponent and some components that are used in the prior art of cochlearimplant processors can be used to perform this function according to thepresent invention. It is important to note that it is the instantaneousamplitude of the waveform at each electrode position which is coded asthe current level (or electric charge or pulse width) of an electricpulse on that electrode. This differs greatly from prior art systemswhere it is the time-averaged amplitude envelope of the waveform whichconstitutes what is coded as the current level of an electric pulse onthat electrode. In essence, the conversion is effected by means of afunction relating the amplitude to electric current level derived fromprior measurements for each electro which may be stored in the memory15.

The present invention can be used with implants that allow bothsimultaneous and/or non-simultaneous stimulation. If the invention isused on an implant that stimulates channels simultaneously, thetraveling wave amplitudes at individual electrode positions can berepresented by simultaneous electric currents (analog rather thanpulsatile stimuli) on each individual electrodes.

If the invention is used with an implant that stimulates channelssequentially (nor-simultaneously), then the Electrical Encodingcomponent can be divided into two sub-components as illustrated in FIG.8. The Sampler component samples the neural excitation pattern such thateach output sample produces one electrical pulse. The Amplitude Mappingcomponent calculates the electrical parameters of the pulse, such ascurrent level and pulse width.

One simple embodiment of the Sampler component is taken from thewell-known Continuous Interleaved Sampling (CIS) processor. The neuralexcitation pattern is sampled in a round-robin fashion at a uniform rateon each channel, so the sampling rate is equal to the simulation rate oneach channel. The samples are interleaved across channels so that theelectrical pulses are sequential (non-overlapping). The rate must besufficiently high so that the time waveform of the neural excitation oneach channel is adequately represented. Typically this requires morethan 1000 pulses per second on each channel.

Note that in a standard CIS processor the filters are designed to benon-overlapping and relatively narrow, and the smoothed envelope of thefilter outputs are sampled. In contrast, the present invention hasbroad, heavily overlapping filters and the instantaneous amplitude ofthe half-wave rectified filter output is sampled.

The CIS Sampler embodiment has the disadvantage that high stimulationrates are required. An alternative embodiment, which is new in thisinvention, is called the Time Interval Maxima Sampler. It reduces thetotal simulation rate that is required. It has the following steps:

1. The neural excitation pattern is divided into short non-overlappingtime intervals. Each time interval can be represented as a matrix X thathas N columns, where N is the number of channels, and T rows, where T isthe number of time samples of the neural excitation pattern in each timeinterval. The duration of the time interval is equal to the time takento output a number M of electrical pulses, where M is less N.

2. In each time interval the maximum value of each channel iscalculated, i.e. the maximum of the matrix X across the rows. The outputis a column vector Y with N columns, one for each channel.

3. The amplitudes of the N samples in column vector Y are examined, andthe M largest samples are retained. Each of these M samples produces oneelectrical pulse. The pulses are output in the next time interval.

The Amplitude Mapping component can be the same as that used in theprior art Continuous Interleaved Sampling (CIS) processor or SpectraMaxima Sound Processor (SMSP). It has the following steps:

1. The amplitude of each sample is compressed by a nonlinear functionknown as a loudness growth function, which typically has a logarithmicshape. Each output P represents a proportion of the electrical dynamicrange.

2. The current level L of each electrical pulse is calculated from theoutput P and the previously measured threshold T and maximum comfortablelevel C (for that channel) as:L=T+(C−T)*P

Following this, the electrode(s) to be stimulated are selected, and theoutput signal generator 16 is fed the data required to produce theelectrical stimulus pulses.

It will be appreciated that there are various ways of implementing thepresent invention, for example using circuitry to provide the travellingwave type stimuli, which are included within the scope of the presentinventive concept. Variations and additions are also possible within thegeneral inventive concept disclosed.

1. A method of processing sound signals for use in generating electricalstimuli for an auditory prosthesis, said method including the steps ofprocessing a sound signal according to a predetermined instruction setto produce a set of stimulus instructions for an implanted electrodearray, characterized in that the predetermined instruction set operatesso as to produce a set of stimulus instructions which, when presented bysaid electrode array, produces a neural excitation pattern whichapproximates the spatio-temporal pattern associated with the travellingwave observed on the basilar membrane in an acoustically excitednormally-hearing cochlea when stimulated with said sound signal.
 2. Amethod according to claim 1 wherein said predetermined instruction setcalculates the travelling wave amplitude variations at each electrodeposition using broad overlapping filters which are not specific only tothe frequencies associated with each electrode position, said filtershaving a shape which is based on one of either the amplitude envelope ofthe acoustic travelling wave in a normal cochlea, or the shape of thepsychophysical tuning curves in a normal cochlea.
 3. A method accordingto claim 2, wherein said method includes the steps of sampling saidsound signal to produce a data sample; deriving the vector of complexFourier transform coefficients for said data sample; multiplying thevector of the coefficients by a complex matrix representing theamplitude and phase of the Fourier frequency components at the positionof the electrodes in the cochlea relative to the amplitude and phase atthe stapes in a normal cochlea to produce an output vector; andconverting the output vector values to a set of stimulus instructions.4. A method according to claim 2 where the group delay of said filtersis adjusted taking into account the time taken for an acoustic signal topropagate from the stapes to each electrode position in an acousticallyexcited normally-hearing cochlea.
 5. A method according to claim 1,wherein said predetermined instruction set includes a model of basilarmembrane motion, said model including determining the phase andamplitude of said sound signal at each electrode position in anacoustically excited normally-hearing cochlea when stimulated with saidsound signal.
 6. A method according to claim 5, wherein saidpredetermined instruction set includes an inner hair cell model, whichcalculates the level of neural excitation at each electrode position inan acoustically excited normally-hearing cochlea when stimulated withsaid sound signal.
 7. A method according to claim 6, wherein said modelis a half-wave rectifier.
 8. A method according to claim 5, wherein saidpredetermined instruction set includes an outer hair cell model, suchthat the effect of the proposed set of stimulus instructions on theresponse of the basilar membrane is fed back to said basilar membranemodel.
 9. A method according to claim 1, wherein the set of stimulusinstructions is based upon the instantaneous amplitude of the waveformat each electrode position.
 10. A method according to claim 9, whereinthe set of stimulus instructions provides a stimulus on an electrodewhen the calculated travelling wave at that electrode position reaches alocal maximum.
 11. A method according to claim 10, wherein if thecalculated travelling wave at the position of more than one electrodereaches a local maximum value at the same time; the electrode with thelarger amplitude value will be stimulated first.
 12. A method accordingto claim 1, in which the predetermined instruction set further includesspecific empirical modifications to improve the perception of speech ormusic in users.
 13. A sound processor for use in a cochlear implantsystem, said sound processor being of the type which receives soundsignals, processes said signals according to a predetermined instructionset, and provides stimulation instructions for an implanted electrodearray, characterized in that the predetermined instruction set operatesso as to produce a set of stimulus instructions which, when presented bysaid electrode array, produces a neural excitation pattern whichapproximates the spatio-temporal pattern associated with the travellingwave observed on the basilar membrane in an acoustically excitednormally-hearing cochlea when stimulated with said sound signal.
 14. Asound processor according to claim 13, wherein said predeterminedinstruction set calculates the travelling wave amplitude variations ateach electrode position using broad overlapping filters which are notspecific only to the frequencies associated with each electrodeposition, said filters having a shape which is based on one of eitherthe amplitude envelope of the acoustic travelling wave in a normalcochlea, or the shape of the psychophysical tuning curves in a normalcochlea.
 15. A sound processor according to claim 14, wherein saidpredetermined instruction set samples said sound signal to produce adata sample; derives the vector of complex Fourier transformcoefficients for said data sample; multiplies the vector of thecoefficients by a complex matrix representing the amplitude and phase ofthe Fourier frequency components at the position of the electrodes inthe cochlea relative to the amplitude and phase at the stapes in anormal cochlea to produce an output vector; and converts the outputvector values to a set of stimulus instructions.
 16. A sound processoraccording to claim 9 wherein the group delay of said filters is adjustedtaking into account the time taken for an acoustic signal to propagatefrom the stapes to each electrode position in an acoustically excitednormally-hearing cochlea.
 17. A sound processor according to claim 13,wherein said predetermined instruction set includes a model of basilarmembrane motion, said model including determining the phase andamplitude of said sound signal at each electrode position in anacoustically excited normally-hearing cochlea when stimulated with saidsound signal.
 18. A sound processor according to claim 17, wherein saidpredetermined instruction set includes an inner hair cell model whichcalculates the level of neural excitation at each electrode position inan acoustically excited normally-hearing cochlea when stimulated withsaid sound signal.
 19. A sound processor according to claim 18, whereinsaid model is a half-wave rectifier.
 20. A sound processor according toclaim 17, wherein said predetermined instruction set includes an outerhair cell model, such that the effect of the proposed set of stimulusinstructions on the response of the basilar membrane is fed back to saidbasilar membrane model.
 21. A sound processor according to claim 13,wherein the set of stimulus instructions is based upon the instantaneousamplitude of the waveform at each electrode position.
 22. A soundprocessor according to claim 21, wherein the set of stimulusinstructions provides a stimulus on an electrode when the calculatedtravelling wave at that electrode position reaches a local maximum. 23.A sound processor according to claim 13, in which the predeterminedinstruction set further includes specific empirical modifications toimprove the perception of speech or music in users.
 24. A methodaccording to claim 13, wherein the set of stimulus instructions providesa stimulus on an electrode when the calculated travelling wave at thatelectrode position reaches a local maximum.
 25. A method according toclaim 14, wherein if the calculated travelling wave at the position ofmore than one electrode reaches a local maximum value at the same time,the electrode with the larger amplitude value will be stimulated first.